v0.2.3

Fix compilation issues on Mac m1.

Best,
Zé Vinícius

Full Changelog: dppalomar/spectralGraphTopology@v0.2.0...v0.2.3

v0.2.2

Minor release that fixes tiny things in order to comply with CRAN.

Best,
Zé Vinícius

Full Changelog: dppalomar/spectralGraphTopology@v0.2.0...v0.2.2

spectralGraphTopology version 0.2.0 (2019-08-10)

This release adds an implementation of the Combinatorial Graph Laplacian (CGL) algorithm for connected graphs proposed by Elgimez, Pavez, and Ortega (2017). This algorithm is implemented in via a function called
learn_combinatorial_graph_laplacian .

The original MATLAB implementation, written by the authors, is available at https://github.com/STAC-USC/Graph_Learning.

Additionally, this implementation of GLE-MM and GLE-ADMM has been polished.

Thanks,
Zé Vinícius

spectralGraphTopology version 0.1.2 (2019-23-09)

Two methods to estimate the Laplacian matrix of connected graphs have been added:

• learn_laplacian_gle_mm, which is based on the majorization-minimization (MM) framework.
• learn_laplacian_gle_admm, which is based on the algorithm named alternating direction method of multipliers (ADMM).

More details about the advantages and shortcomings of these two algorithms may be seen here:

• Licheng Zhao, Yiwei Wang, Sandeep Kumar, and Daniel P. Palomar, Optimization Algorithms for Graph Laplacian Estimation via ADMM and MM, IEEE Trans. on Signal Processing, vol. 67, no. 16, pp. 4231-4244, Aug. 2019

spectralGraphTopology version 0.1.1 (2019-01-07)

• Minor changes in the DESCRIPTION file to conform with CRAN.

• Initial release version 0.1.0 was on CRAN on 2019-05-08.